Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

FAIR Data, Operations and Model management for Systems Biology and Systems Medicine Projects

896 views

Published on

FAIR Data, Operations and Model management for Systems Biology and Systems Medicine Projects given at 1st Conference of the European Association of Systems Medicine, 26-28 October 2016, Berlin. the FAIRDOM project is described.

Published in: Science
  • Be the first to comment

  • Be the first to like this

FAIR Data, Operations and Model management for Systems Biology and Systems Medicine Projects

  1. 1. FAIR Data, Operations and Model management for Systems Biology and Systems Medicine Projects Prof Carole Goble The FAIRDOM Consortium carole.goble@manchester.ac.uk http://fair-dom.org, http://fairdomhub.org 1st Conference of the European Association of Systems Medicine, 26-28 October 2016, Berlin
  2. 2. Asset Management and Sharing • Access to public funded research • Reproducible results • Value and cite all research outcomes • Sustained data infrastructure
  3. 3. Findable Accessible Interoperable Reusable (Intelligible) (Reproducible) (Citable) (Trackable) https://www.force11.org/group/fairgroup/fairprinciples
  4. 4. Projects .... and Programmes.... funder and research project legacy • Reuse • Compliance • Retention • Dissemination • Collaboration • Reproducibility • Resource & Skills Limitations
  5. 5. Findable Accessible Interoperable Reusable Data Operations Models Sponsors
  6. 6. FAIRDOM Association e.V. Partners open innovation, not for profit LifeGlimmer GmBH SB-ScienceManagement GmBH New Forest Ventures Ltd
  7. 7. FAIRDOM Pillars Project Support Community Actions Platforms,Tools Public Project Commons
  8. 8. Systems Approach… people, assets, processes pragmatics • Multiple, interrelated assets • Multiple, dispersed repositories • Multi-partner, -discipline projects • Team science practices • Experiment – Asset lifecycles • Academic innovation drivers
  9. 9. Multiple, interrelated assets structured formats, standards, ontologies context Analytics & Pipelines Literature SBML, CellML, PharmML Matlab, Mathematica Fortran, R, Python SOPS Multiple omics: genomics, transcriptomics proteomics, metabolomics fluxomics, reactomics Images Reaction kinetics Samples, Specimens, Strains Human data STANDARDS versioning, tracking: provenance, parameters, citation Operations Data SOPs Models
  10. 10. FAIRData and Metadata Standards that help to improve understanding and exchange…. Nicolas Le Novère, Babraham Institute, UK.
  11. 11. …researchers do not always use them.... Format MetadataMetadata Ontologies *top three most popular The evolution of standards and data management practices in systems biology (2015). Stanford et al, Molecular Systems Biology, 11(12):851
  12. 12. … makes model reuse tricky… Stanford et alThe evolution of standards and data management practices in systems biology, Molecular Systems Biology (2015) 11: 851 DOI 10.15252/msb.20156053
  13. 13. Specialist Public Repositories General archives Multi Repository Repertoire Access, Reuse Local Data Stores The evolution of standards and data management practices in systems biology (2015). Stanford et al, Molecular Systems Biology, 11(12):851
  14. 14. sharing/publishing assets in public archives… Data Models *top three most popular The evolution of standards and data management practices in systems biology (2015). Stanford et al, Molecular Systems Biology, 11(12):851
  15. 15. Multi-partner, multi-disciplinary projects where sharing and metadata collection isn’t second nature Consortia Grp 3 Grp 1 Grp 2
  16. 16. Multi-partner, multi-disciplinary projects SOPs andYellow Pages top request… What methods are been used to determine enzyme activity? What SOP was used for this sample? Where is the validation data for this model? Is there any group generating kinetic data? Is this data available? Track versions of my model Whats the relationship between the data and model? Which data belong to which publications?
  17. 17. Downstream assets discovery and sharing Organisation Communication Dissemination Navigate through assets Reuse later Enable team to reuse/ reproduce Help others find out Reuse with new partners Tell more, take credit Standardised metadata practices Assets
  18. 18. Find… own hard disk for storage… The evolution of standards and data management practices in systems biology (2015). Stanford et al, Molecular Systems Biology, 11(12):851
  19. 19. Samiul Hasan, GSK Biocuration need in Pharma: Drivers from a Translational Bioinformatics Perspective, Poster S16
  20. 20. The FAIR Project Challenge Track collection of data and metadata X X Maintain experimental context X Find and exchange assets X X Long-term retain results beyond a project X X X Share, disseminate and publish assets sensitively X X X Consistently report for interpretation, interoperability & comparison X X Promote standardised metadata practices. X X Organise and link assets X X X Reuse tools and community archives X Integrate with other data stores and platforms X X Support reproducible publications X X X X Credit owners X X
  21. 21. FAIRDOM Pillars Project Support Community Actions Platforms,Tools Public Project Commons
  22. 22. Community, Knowledge Hub http://www.fair-dom.org Know-how,Guides,Templates,Workshops,Training, Webinars, Standards and Policy Forums
  23. 23. Project Support Processes, Practices, People…take time and persuasion Community support Specialprojectsupport Specialprojectsupport PALs project ambassadors best practices, forums, training curation handholding SBML model technical curation
  24. 24. Asset Management Platforms an ecosystem of resources Front end Web based rich interface Catalogue and Commons All about the metadata Results repository http://seek4science.org Back end Scaled LIMS and analytics Auto-archiving Instruments data repository https://sis.id.ethz.ch/software/openbis.html
  25. 25. A community Commons…. self managed workspaces Controlled sharing and publishing
  26. 26. • Licenses • Negotiated access • Embargos • Permission controls • Staged sharing • Private walled gardens FAIR Play Practices Using FAIRDOM my own lab colleagues saw what I was doing and called to collaborate! Jurgen Hannstra Vrije Universiteit Amsterdam, Netherlands
  27. 27. Investigation Study Analysis Data Model SOP(Assay) ….organised in an ISA (Investigation, Study, Assay/Analysis) format.
  28. 28. Packaging Retaining Context Supporting Decision making
  29. 29. STUDY ASSAYINVESTIGATION Experimental assay Modeling assay Publication [Maksim Zakhartsev]
  30. 30. ... a “Research Object” Catalogue metadata aggregated across repositories retaining context to support decision making and reuse Local Stores External Databases Publishing services Secure Stores Model Resources
  31. 31. … with integrated tooling metadata annotation against standards model validation, comparison and simulation SBML Model simulation Model comparison Model versioning Reproducing simulations [Jacky Snoep, Dagmar Waltemath, Martin Peters, Martin Scharm]
  32. 32. Retaining context, supporting decision making Towards data harmonisation and indexing [Susanna Sansone]
  33. 33. Stealthy Ramps for helping with Metadata Standards Tooling for annotations and templates for different types of assay data towards data harmonisation. Incentive by side effect. Embed ontologies into Excel templates Excel spreadsheets enriched with ontology annotations Upload, extract metadata and register http://www.rightfield.org.uk
  34. 34. Exchange and Publishing Supplementary information Annotation file Stoichiometric matrix SBML Stationary fluxes [Maxim Zakhartsev]
  35. 35. https://doi.org/10.15490/seek.1.investigation.56 Penkler et al (2015) FEBSJ 282:1481-1511.
  36. 36. Reproducible Exchange and Publishing and better credit Author List: Joe Bloggs; Jane Doe Title: My Investigation Date: September 2016 DOI: https://doi.org/10.15490/seek## information travels with the data and models
  37. 37. FAIRDOM-SEEK local or public commons *Troup, E.; Clark, I; Swain, P; Millar, AJ; Zielinski,T (2015) Practical evaluation of SEEK and openBIS for biological data management in SynthSys http://hdl.handle.net/1842/12236 FAIRDOMHub.org Vrije Universiteit Yellow Pages
  38. 38. IMOMESIC pathway Integrating Modelling of Metabolism and Signalling towards an Application in Liver Cancer https://fairdomhub.org/projects/24 [Ursula Klingmüller, Martin Böhm]
  39. 39. What about FAIR Systems Medicine? OlafWolkenhauer et al, Enabling multiscale modeling in systems medicine, Genome Medicine 2014 6:21* 1. Samples 2. Access to sensitive data 3. Multi-models *DOI: 10.1186/gm538, http://genomemedicine.com/content/6/3/21
  40. 40. Samples metadata framework BBMRI, ELIXIR, Biosamples, FAIRDOM, UKCRCTissue Directory, UK Synthetic Biology Centres User defined sample models Interlinking between sample types Sample type defines a sharable standard Tied to assay processes
  41. 41. FAIR Sensitive Data, certified repositories walled gardens and registration flags for Catalogue legal restrictions for sharing anonymised and non-anonymized data Open Data Register metadata Upload data Register link Register access method Register metadata Register access method Local AAI service Register metadata Closed Data Closed Data
  42. 42. Model Laissez-Faire • Navigation between • Single standards at 1 scale • Multi-model hosting Linking models…. • connecting (experimental/simulation) data to models • connecting the single standards? • interfacing between the different scales?
  43. 43. In summary…Pragmatic FAIR support for projects people, assets, processes • Multiple, interrelated assets • Multiple, dispersed repositories • Multi-partner, -discipline projects • Multiple community tools • Team science practices • Experiment – Asset lifecycles • Academic innovation drivers meta data Standards-based tools
  44. 44. Challenges to FAIR Asset Management Free Puppies
  45. 45. FAIR Play microscopes -> data scopes, sharing citizenship, incentives by side effects PI leadership Sticking to conventions Local responsibility Time and resource Curation recognition Trust • Tribal trading behaviours • Enclave sharing • Not public donation • Reciprocity & credit Drivers … • External dominate • Personal productivity affecting behavioural change through libertarian paternalism [Kristian Garza]
  46. 46. Jon OlavVik, Norwegian University of Life Science Maksim Zakhartsev University Hohenheim, Stuttgart, Germany Alexey Kolodkin Siberian Branch Russian Academy of Sciences Tomasz Zieliński, SynthSys Centre University Edinburgh, UK Martin Peters, Martin Scharm Systems Biology Bioinformatics University of Rostock, Germany
  47. 47. 3rd Foundry meeting, Dec 1-2 2016 Frankfurt Developers Foundry Support developers of Systems Biology tools and platforms

×